Within the digital marketing world, agencies and brand owners are racing to explore how they can leverage the full potential of artificial intelligence (AI) and machine learning (ML) in order to reach their marketing goals. In fact, according to one estimate, 84 percent of marketing organizations are implementing or expanding their AI and ML programs in 2019. And for good reason – initial results show that machine learning can help to boost customer satisfaction, increase sales, and improve overall engagement around new product offerings.
The Customer Experience and Customer Satisfaction
Currently, the hottest area of adoption for machine learning involves chatbots and virtual assistants. The traditional model of customer service – in which one representative connects with one customer at one time – is changing rapidly. Thanks to AI-powered chatbots, it’s no longer the case that you need to queue up to talk to a customer service representative or wait for longer periods of time on the phone to talk to a “live” person. Most chatbots and virtual assistants are able to answer the types of basic questions that most customers have, freeing up human representatives to answer the most complex and challenging questions.
Real-Time Personalized Advertising
In the best of all possible worlds, marketers would be able to deliver personalized, real-time messages to every single customer. Think about the current marketing model – in which a 30-second TV spot or web banner is designed to appeal to as many people as possible. With AI and ML, it’s possible to craft personalized ads and marketing messages based on what computers know about your likes, interests, behaviors, and preferences. And they can deliver these ads and messages at precisely the right time. (Although, admittedly, it can get a little creepy when it feels like someone has been tracking and monitoring you for days on end….)
At the very least, marketers can help to address the problem of customer churn. Based on sophisticated models and algorithms, machines can predict when a customer is just about ready to defect to a rival competitor, and then craft a perfectly timed offer to keep the customer. This can help to boost the customer lifetime value of every single customer and improve the overall efficiency of high-churn industries.
Product and Price Optimization
Just a few years ago, marketers had to guess what types of features, options, or pricing would appeal to customers and prospects. Now, thanks to machine learning and the ability to evaluate hundreds of factors at one time, it’s possible to create a much more streamlined product development process. Marketers can still use customer surveys and polls to figure out what customers want, but they can also make use of all the unstructured data on the web to see what customers are actually reviewing, liking and buying. And that, of course, is good for the long-run bottom line. The goal of marketing is to sell more products, right?
Look for AI and machine learning to remain hot topics throughout 2020. As long as new AI-powered solutions are showing signs that they can move the needle when it comes to key metrics and indicators, then it’s a good bet that marketers will continue to experiment with this rapidly developing technology.
Personalization and sending the right message at the right time are key tools for modern marketers. However, to personalize and know the right time to send requires the right data. How well do you really know your customers? And what can help? Many marketers have found a customer data platform (CDP) useful in creating a single, unified customer profile. Find out how to “Do More with Customer Data Platforms.”
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